CX + AI: Balancing a Human Touch with Machine Learning
Artificial intelligence (AI) is particularly impactful in the provision of personalisation and efficiency for a customer’s experience. This blog post looks into a couple of developing AI trends that have had an important impact on customer experience.
Natural Language Processing
Machine learning is a type of artificial intelligence that enables software applications to become more accurate in forecasting outcomes without being specially programmed. It has been around for centuries, but its adoption into our everyday lives and common parlance has truly developed in the 21st century. Its growth has accelerated since the likes of IBM’s Watson, Apple’s Siri, and Amazon’s Alexa introduced natural language processing (NLP) to the mainstream.
NLP allows for computers to recognise the nuances in human speech and writing, automating our understanding of commentary as positive, negative or neutral. The main idea of machine learning is to create algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable range. By using NLP, companies are able to better understand their customers’ experiences and fix any problems in their business processes that trigger unhappy customer interactions.
Chatbots
Google and similar search engines have altered customer expectations, such that they anticipate accurate answers quickly – businesses need to keep up with their demands to stay in their favour. Enter the chatbot. Chatbots can answer routine customer queries at any time, without the burdens of queues or time restraints that plague contact centres, freeing your employees to help the customers with more demanding questions.
It is worth noting that chatbots cannot think or problem solve. They are programmed to answer routine customer questions through machine learning, so they cannot replace your contact centre staff. As more data is introduced to a system, the computer will grow to be smarter and more intuitive, but this is by no means fool proof. Introducing chatbots to your business can lessen the burden placed on your staff, with more straightforward customer questions being handled by bots while questions that require more nuanced feedback still go to the real agents.
What AI Can’t Do
Computers lack empathy and you cannot use AI to measure what someone feels in terms of their emotional reaction to an experience. While you can use AI to make inferences about the level of service that somebody has experienced, it is difficult to understand how they truly felt without feedback.
We are still in a period of narrow AI although general AI may be on the horizon with companies like DeepMind leading the charge. The AI used today is limited, able only to perform specific tasks, and nothing like a truly human like machine has been developed. Development is expensive and computers don’t quite have the processing power for the introduction of a HAL to the real world yet.
Conclusion
At this moment in time, and certainly for the foreseeable future, the most productive way to introduce AI to your customer experience development is to adopt a blended AI approach, which combines a human element with machine learning. This strategy will reduce the cost of servicing customers and improve outcomes with humans still playing an integral role in the CX process. There seems to be a consensus that a hybrid of machine and human interaction will deliver the best CX outcomes, certainly in the short to medium term, it’s hard to disagree with that.
